JPH0438457A - Apparatus for inspecting surface state - Google Patents

Abstract

PURPOSE:To estimate the inferiority mixing ratio of a group of objects to be inspected and to inspect the uniformity of the surface state thereof by obtaining a large number of adaptation coefficients F with respect to the successively inputted image data of the objects to be inspected to form the frequency distribution thereof and comparing the standard deviation thereof with the relation between preset standard deviation and an inferiority mixing ratio. CONSTITUTION:A large number of adaptation coefficients F corresponding to the difference between the density histograms to take image data and the theoretical frequencies of respective densities according to regular distribution having the mean value and standard deviation of the density histograms are calculated by operational processing carried out with respect to the image data of objects to be inspected successively inputted from an imaging apparatus to calculate the frequency distribution and standard deviation Fsigma thereof. The standard deviation Fsigma is compared with the relation between the standard deviation and inferiority mixing ratio preset corresponding to the surface states of the objects to be inspected of this time to estimate the inferiority mixing ratio of a group of the objects to be inspected to inspect the uniformity of the surface state of said group.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a surface condition inspection device that detects surface conditions such as scratches, dust, roughness, and color unevenness (shading of color tone) existing on a surface.

[Prior art] Conventionally, as a surface flaw inspection device, He was applied to the surface of an object to be inspected.
-Ne laser light is irradiated, and the presence of scratches on the surface is detected based on the degree to which the laser beam is scattered by the unevenness of the scratches.

[Problems to be Solved by the Invention] However, the above conventional surface flaw inspection apparatus using the light irradiation-scattering method has the following problems (1) to (4).

■The optical system is complex and the device is large.

■Surface conditions such as color unevenness that are not accompanied by surface irregularities cannot be detected.

■Detection results do not necessarily match the sense perceived by the human eye.

An object of the present invention is to use a compact device configuration to reliably inspect surface conditions, including color irregularities, with a sense similar to that of humans.

[Means for Solving the Problems] The present invention provides an imaging device that images the surface of an object to be inspected, a verification device that verifies the surface state of the object to be inspected based on the imaging result of the imaging device, and a verification device for the verification device. The verification device calculates a density histogram n (K) for the image data captured by the imaging device, and calculates the density histogram n (K) for the image data captured by the imaging device.
(K), find the average value μ and standard deviation σ based on the above average value μ and standard deviation σ, find the theoretical frequency g (K) of each concentration that follows a normal distribution with the above mean value μ and standard deviation σ, and calculate the above concentration histogram n (to) and the above theory. A large number of compatibility coefficients can be obtained by determining a compatibility coefficient F corresponding to the difference from the frequency g (K), and performing the calculation operation to obtain this compatibility coefficient F on image data of each subject that is input one after another from an imaging device. Obtain F, create its frequency distribution, find the standard deviation Fσ of the frequency distribution, and calculate the standard deviation F
The defective contamination rate of the group of objects to be inspected is estimated by comparing σ with the relationship between the standard deviation and defective contamination rate, which has been set in advance in accordance with the surface condition to be tested, and the It is designed to test the uniformity of the surface condition.

[Effect] According to the present invention, the following effects (1) to (4) are achieved.

■The surface condition can be detected using a versatile imaging device such as a television camera, and the device configuration can be made compact.

■Since the surface condition is detected based on the surface concentration distribution, it is possible to detect the surface condition, including color unevenness, with a sense similar to that of humans.

■Concentration histogram n (
compatibility coefficient F corresponding to the difference between K) and the theoretical frequency g (K)
, find the standard deviation Fσ of the frequency distribution, and compare this standard deviation Fσ with the relationship between the standard deviation and the defective contamination rate, which has been set in advance according to the surface condition to be inspected. It was decided to estimate the defective contamination rate of the group of test objects and test the uniformity of the surface condition of the group of test objects. Thereby, the surface condition of the object to be inspected can be reliably inspected with high precision.

[Example] Fig. 1 is a block diagram showing an example of the inspection device of the present invention, Fig. 2 is a schematic diagram showing image data, Fig. 3 is a flowchart showing the inspection procedure according to the present invention, and Fig. 4 is a compatibility coefficient. FIG. 2 is a correlation diagram showing the relationship between the standard deviation of the frequency distribution and the defective inclusion rate.

The surface condition inspection device W1 includes a television camera 10 (imaging device).
, an inspection bag 'l120, and an output bag fi30, and inspects the surface of an object to be inspected, such as a thermoplastic foam sheet, for abnormalities.

The basic operations of the surface condition inspection device 1 are as follows (1) to (4)
It is.

(1) The surface of the foam sheet is imaged by the television camera 10.

The television camera 10 transfers a multivalued image sampled pixel by pixel to the test device 20.

(2) The verification device 20 converts the image data of the television camera 1o into an A/D converter 21, for example, at 8-bi soto (256 gradations).
, to create a digital image of MXN pixels, which is input to the image memory 22.

(3) Based on the image input to the image memory 22, the testing device 20 uses the CPO 23 to test whether there is any abnormality on the surface.

(4) The output device 30 displays the test results of the test device 20 and generates an alarm if necessary.

Note that as the imaging device (10), a line sensor having M spatial resolution may be used instead of the television camera. In this case, the line sensor and the object to be inspected are moved relative to each other, N groups of data are stored in the image memory.

The verification device 20 does not necessarily use the image memory 22, and the
The output data of the /D converter 21 may be input directly to the CPU 23.

However, the verification operation by the verification device 20 is as follows.
This is done as follows (see Figure 3).

(2) Obtain a density histogram n(k) for the image data of MXN pixels (k=density value, n: frequency).

When creating this density histogram n(k), depending on the size of the abnormal part predicted in advance in the test object or the sampling density by the television camera 10, it may be possible to create the density histogram n(k) without using the MXNXN pixel tube input to the verification device 20. Among them, mXn (05M, n≦N) pixels (see Figure 2 (A)), or pixels where N is an even number (Figure 2 (B)
) may also be used as part of the MXN pixels.

■Average each density value next to each other to make the histogram smooth. For example, the frequency n' (K) for the concentration value is n' (K) = [n (k-2) + 2 n
(K-1)+3 n (K) +2 n (K+1)
+ n (k+2) ] / 9 ... (1
).

(2) Based on the averaged density histogram n' (K), find its average value μ and standard deviation σ.

Σ-n' (K) Σn' (K) ...(
3) ■ Calculate the theoretical frequency g (K) of each concentration according to the normal distribution N (μ, σ2) with the average value μ and standard deviation σ of the concentration histogram n ′ (K).

■Concentration histogram n' (K) and theoretical frequency g (K
) is calculated using the following formula (4) or (5).
) is calculated using the formula. However, this compatibility coefficient F is g (K
)≠0, and in equations (4) and (5), if β-bit quantization is performed, L=2j2-1.

g (K) ... (4) g (K) ... (5) ■ The calculation operation to obtain the conformity coefficient F of (■) above is performed using the TV camera 10.
A large number of conformity coefficients F are obtained by performing this on the image data of each subject to be inspected that are input one after another from , and a frequency distribution thereof is created.

■Determine the standard deviation Fσ of the frequency distribution obtained in step (■) above, and compare the standard deviation Fσ with the relationship between the standard deviation and the defective contamination rate, which has been set in advance according to the surface condition to be tested this time. The defect contamination rate of the group of objects to be inspected is estimated, the uniformity of the surface condition of the group of objects to be inspected is verified, and the results are output (see FIG. 4). Here, "r defective mixture rate" refers to the proportion of the imaged portion that is considered to be defective. Regarding "uniformity", if the defective mixture rate is smaller than a predetermined value, it is determined that the product is uniform.

The correlation diagram shown in FIG. 4 is obtained by determining the compatibility coefficients for good/defective samples (a large number of samples) and mixing them in an arbitrary ratio to determine the relationship.

Next, the operation of the above embodiment will be explained.

- Surface conditions can be detected using a versatile imaging device such as the television camera 10, and the device configuration can be made compact.

Moreover, the processing contents are simple, and the surface condition can be verified in a short time, and the inspection can be completed even on the conveyance line of the object to be inspected.

Since the surface condition is detected based on the concentration distribution state of the 0 surface, the surface condition including color unevenness etc. can be detected with a sense similar to that of humans.

■Density histogram n' for a large number of image data
(K) and the theoretical frequency g (Kl), find the standard deviation Fσ of the frequency distribution, and set the standard deviation Fσ in advance according to the surface condition to be tested this time. In light of the relationship between the standard deviation and the defective contamination rate, we estimated the defective contamination rate of the group of inspected objects and tested the uniformity of the surface condition of the group of inspected objects. The surface condition of the object to be inspected can be reliably inspected with high precision.

[Effects of the Invention] As described above, according to the present invention, surface conditions including color unevenness can be reliably inspected with a sensation similar to that of a human being, using a compact device configuration.

[Brief explanation of the drawing]

Fig. 1 is a plot diagram showing an example of the inspection device of the present invention, Fig. 2 is a schematic diagram showing image data, Fig. 3 is a flowchart showing the inspection procedure according to the present invention, and Fig. 4 is a frequency distribution of conformity coefficients. FIG. 3 is a correlation diagram showing the relationship between the standard deviation of the standard deviation and the defective mixture rate. 10... Imaging device, 20... Verification device, 30... Output device. Patent applicant: Sekisui Chemical Co., Ltd. Representative Hiroshi 1) Kaoru Figure 3

Claims (1)

[Claims] (1) It has an imaging device that images the surface of the object to be inspected, a test device that tests the surface condition of the test object based on the imaging results of the imaging device, and an output device that outputs the test results of the test device. The verification device calculates a density histogram n(K) for the image data captured by the imaging device, and calculates the average value μ and standard deviation σ based on the density histogram n(K). The theoretical frequency g(K
) is calculated, and a fitting coefficient F corresponding to the difference between the density histogram n(K) and the theoretical frequency g(K) is calculated, and the calculation operation for calculating the fitting coefficient F is performed for each image input one after another from the imaging device. By performing this on the image data of the inspection object, a large number of conformity coefficients F are obtained, a frequency distribution is created, the standard deviation Fσ of the frequency distribution is determined, and the standard deviation Fσ is determined to correspond to the surface condition to be tested this time. The method estimates the defective contamination rate of a group of objects to be inspected in light of the relationship between the standard deviation and the defective contamination rate that has been set in advance, and tests the uniformity of the surface condition of the group of objects to be inspected. Condition inspection device.